{
  "abstract": "As quantum processors scale, online calibration, quantum error correction (QEC), and measurement-driven feedback require continuous classical processing and parameter updates. Sharing on-chip resources reduces hardware cost, but computation completion, the last parameter read, and result consumption occur at different times. Their dependencies must be managed separately while preserving quantum operations' real-time requirements. We present QCORE, a quantum-computing-oriented, resource-efficient runtime architecture that coordinates these lifecycles for safe resource reuse and parameter consistency. QCORE models resource occupancy, parameter protection, and consumer dependencies as independent lifecycles and provides three mechanisms: pre-use checks and parameter binding to verify timing, identity, and dependencies; access-aware protection through value snapshots, version references, or active-configuration windows; and joint admission of resource reservations and parameter installation. After request submission, hardware autonomously handles admission, protection, installation, and reclamation, reducing fine-grained Host coordination and providing a foundation for one Host to manage multiple controllers. We implement synthesizable RTL and validate FPGA timing at 100 MHz. Independent release reduces whole-program execution time by 16.83% in Ramsey calibration and QEC replay. Joint admission increases on-time completions from 5/15 to 15/15 under contention across five arrival phases. Under identical external deadlines, a shared NN backend reduces LUT usage by 12.28%-13.81% and DSP usage by 39.39% compared with two statically assigned backends. These results show that lifecycle coordination exploits inter-task timing slack for on-chip sharing, increasing service capacity under limited resources.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2608.06875",
  "author_total": 8,
  "authors": [
    {
      "name": "Heyue Li"
    },
    {
      "name": "Shaolin Xiang"
    },
    {
      "name": "Tian Tian"
    },
    {
      "name": "Qichun Liu"
    },
    {
      "name": "Tiefu Li"
    },
    {
      "name": "Zhihua Wang"
    },
    {
      "name": "Yanshu Guo"
    },
    {
      "name": "Hanjun Jiang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/19p87bfk28tbd.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2608.06875",
  "fulltext_url": null,
  "id": "19p87bfk28tbd",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2608.06875",
  "language": null,
  "licence": "CC-BY-NC-SA-4.0",
  "licence_label": "CC BY-NC-SA 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by-nc-sa/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cs.AR"
    ],
    [
      "arxiv",
      "quant-ph"
    ],
    [
      "openalex",
      "1702|Quantum Computing Algorithms and Architecture"
    ]
  ],
  "openalex": "W7202118428",
  "pdf_url": "https://arxiv.org/pdf/2608.06875",
  "pmcid": null,
  "pmid": null,
  "published": "2026-11-09",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/19p87bfk28tbd.ris",
  "sources": [
    {
      "first_seen": "2026-11-10T06:21:23Z",
      "native_id": "2608.06875",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2608.06875"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:quant-ph",
      "subfield": "quantum"
    }
  ],
  "title": "QCORE: A Quantum-Computing-Oriented,Resource-Efficient Runtime Architecture with Lifecycle Coordination",
  "title_text": "QCORE: A Quantum-Computing-Oriented,Resource-Efficient Runtime Architecture with Lifecycle Coordination",
  "type": "preprint",
  "updated_at": "2026-11-10T06:21:23Z",
  "url": "https://research.draconitic.com/paper/19p87bfk28tbd",
  "venue": "arXiv",
  "versions": []
}